CARDIOTORACIC RADIOLOGICAL IMAGING AND THE ROLE OF ARTIFICIAL INTELLIGENCE IN COVID-19

Öz

ABSTRACT Much has been learned since the findings of Covid-19's imaging were published in early 2020. Many classification systems have been developed based on characteristic imaging findings to report imaging studies. As a result of increased performance in imaging and improved access to RT-PCR (Reverse Transcriptase-Polymerase Chain Reaction) testing, imaging is only indicated for patients with more severe disease or worsening breathing. Although the infection occurs in a spectrum ranging from asymptomatic to severe and sometimes fatal disease, acute lung injury is the most common. Imaging initially emerged with CT (Computed Tomography) as an alternative and subsequently played a more limited role based on specific indications, possibly as a superior test compared to RT-PCR. Various classification and reporting schemes have been developed for triage in cases where RT-PCR availability is limited and its performance is uncertain. Interobserver agreement for features with typical findings unique to Covid-19 and features that suggest an alternative diagnosis is high in a large number of studies. Some studies evaluating the degree of lung involvement on chest X-ray and CT have correlated with critical illness and the need for mechanical ventilation. In addition to pulmonary manifestations, cardiovascular complications such as thromboembolism and myocarditis have sometimes been attributed to Covid-19, which contributes to neurological and abdominal manifestations. Finally, artificial intelligence shows promise in both the diagnosis and prognosis of Covid-19 pneumonia in terms of both radiography and CT.

Anahtar Kelimeler

• Covid 19
• Artificial intelligence
• Computed tomography
• Chest radiography
• RT-PCR

COVID-19’DA KARDİYOTORASİK RADYOLOJİK GÖRÜNTÜLEME VE YAPAY ZEKANIN ROLÜ

Öz

ÖZET Covid-19'un görüntülemesiyle ilgili bulgular 2020'nin başlarında yayınlandığından beri çok şey öğrenildi. Görüntüleme çalışmalarını bildirmek için birçok sınıflandırma sistemi, karakteristik görüntüleme bulgularına dayanarak geliştirilmiştir. Görüntülemedeki artmış performans ve RT-PCR (Revers Transkriptaz-Polimeraz Zincir Reaksiyonu) testine erişimin kolaylaşması sonucu görüntüleme yalnızca daha şiddetli hastalığı olan veya solunumu kötüleşen hastalar için endikedir. Enfeksiyon, asemptomatik tablodan şiddetli ve bazen ölümcül hastalığa kadar değişen bir spektrumda ortaya çıkmakla beraber, en sık akut akciğer hasarı görülür. Görüntüleme başlangıçta alternatif olarak BT (Bilgisayarlı Tomografi) ile ortaya çıkıp sonradan muhtemelen RT-PCR'na kıyasla daha üstün bir test olarak, spesifik endikasyonlara dayalı daha sınırlı bir rol almıştır. Salgının başlarında, Covid-19 şüphesi olan hastalar için, RT-PCR testinin kullanılabilirliğinin sınırlı olduğu ve performansının belirsiz olduğu durumlarda triyaj amacıyla göğüs görüntüleme için çeşitli sınıflandırma ve raporlama şemaları geliştirilmiştir. Covid-19'a özgü tipik bulgulara sahip özellikler ve alternatif bir tanıyı öneren özellikler için gözlemciler arası anlaşma, çok sayıda çalışmada yüksektir. Göğüs grafisi (GG) ve BT'deki akciğer tutulumunun derecesini değerlendiren bazı çalışmalar, kritik hastalık ve mekanik ventilasyon ihtiyacı ile korelasyon göstermiştir. Pulmoner belirtilere ek olarak, tromboembolizm ve miyokardit gibi kardiyovasküler komplikasyonlar, bazen nörolojik ve abdominal belirtilere katkıda bulunan Covid-19'a atfedilmiştir. Son olarak yapay zeka, hem radyografi hem de BT açısından Covid-19 pnömonisinin hem tanı hem de prognozunda umut vadetmektedir.

Anahtar Kelimeler

• Covid 19
• Yapay zeka
• Bilgisayarlı tomografi
• Göğüs grafisi
• RT-PCR

Kaynakça

1. 1. Kanne JP. Chest CT findings in 2019 novel coronavirus (2019-nCoV) infections from Wuhan, China: key points for the radiologist. Radiological Society of North America; 2020.
2. 2. Kanne JP, Little BP, Chung JH, Elicker BM, Ketai LH. Essentials for radiologists on COVID-19: an update—radiology scientific expert panel. Radiological Society of North America; 2020.
3. 3. Sharma A, Eisen JE, Shepard J-AO, Bernheim A, Little BP. Case 25-2020: A 47-Year-Old Woman with a Lung Mass. New England Journal of Medicine. 2020;383(7):665-74.
4. 4. Radiology A. ACR recommendations for the use of chest radiography and computed tomography (CT) for suspected COVID-19. Infection. ACR website. 2020.
5. 5. Lang M, Som A, Mendoza DP, Flores EJ, Li MD, Shepard J-AO, et al. Detection of unsuspected coronavirus disease 2019 cases by computed tomography and retrospective implementation of the Radiological Society of North America/Society of Thoracic Radiology/American College of Radiology consensus guidelines. Journal of thoracic imaging. 2020;35(6):346-53.
6. 6. Rubin GD, Ryerson CJ, Haramati LB, Sverzellati N, Kanne JP, Raoof S, et al. The role of chest imaging in patient management during the COVID-19 pandemic: a multinational consensus statement from the Fleischner Society. Chest. 2020;158(1):106-16.
7. 7. Goyal N, Chung M, Bernheim A, Keir G, Mei X, Huang M, et al. Computed tomography features of coronavirus disease 2019 (COVID-19): a review for radiologists. Journal of thoracic imaging. 2020;35(4):211-8.
8. 8. Wong HYF, Lam HYS, Fong AH-T, Leung ST, Chin TW-Y, Lo CSY, et al. Frequency and distribution of chest radiographic findings in patients positive for COVID-19. Radiology. 2020;296(2):E72-E8.

9. 9. Jacobi A, Chung M, Bernheim A, Eber C. Portable chest X-ray in coronavirus disease-19 (COVID-19): A pictorial review. Clinical imaging. 2020.
10. 10. Toussie D, Voutsinas N, Finkelstein M, Cedillo MA, Manna S, Maron SZ, et al. Clinical and chest radiography features determine patient outcomes in young and middle-aged adults with COVID-19. Radiology. 2020;297(1):E197-E206.
11. 11. Chung M, Bernheim A, Mei X, Zhang N, Huang M, Zeng X, et al. CT imaging features of 2019 novel coronavirus (2019-nCoV). Radiology. 2020;295(1):202-7.
12. 12. Simpson S, Kay FU, Abbara S, Bhalla S, Chung JH, Chung M, et al. Radiological Society of North America Expert Consensus Statement on Reporting Chest CT Findings Related to COVID-19. Endorsed by the Society of Thoracic Radiology, the American College of Radiology, and RSNA. Radiology: Cardiothoracic Imaging. 2020;2(2):e200152.
13. 13. McGuinness G, Zhan C, Rosenberg N, Azour L, Wickstrom M, Mason DM, et al. Increased incidence of barotrauma in patients with COVID-19 on invasive mechanical ventilation. Radiology. 2020;297(2):E252-E62.
14. 14. Bernheim A, Mei X, Huang M, Yang Y, Fayad ZA, Zhang N, et al. Chest CT findings in coronavirus disease-19 (COVID-19): relationship to duration of infection. Radiology. 2020:200463.
15. 15. Pan F, Ye T, Sun P, Gui S, Liang B, Li L, et al. Time course of lung changes at chest CT during recovery from coronavirus disease 2019 (COVID-19). Radiology. 2020;295(3):715-21.
16. 16. Pan Y, Guan H, Zhou S, Wang Y, Li Q, Zhu T, et al. Initial CT findings and temporal changes in patients with the novel coronavirus pneumonia (2019-nCoV): a study of 63 patients in Wuhan, China. European radiology. 2020;30(6):3306-9.
17. 17. Ruch Y, Kaeuffer C, Ohana M, Labani A, Fabacher T, Bilbault P, et al. CT lung lesions as predictors of early death or ICU admission in COVID-19 patients. Clinical Microbiology and Infection. 2020;26(10):1417. e5-. e8.
18. 18. Yin X, Min X, Nan Y, Feng Z, Li B, Cai W, et al. Assessment of the severity of coronavirus disease: quantitative computed tomography parameters versus semiquantitative visual score. Korean journal of radiology. 2020;21(8):998.
19. 19. Pu J, Leader JK, Bandos A, Ke S, Wang J, Shi J, et al. Automated quantification of COVID-19 severity and progression using chest CT images. European Radiology. 2021;31(1):436-46.
20. 20. Huang L, Han R, Ai T, Yu P, Kang H, Tao Q, et al. Serial quantitative chest CT assessment of COVID-19: a deep learning approach. Radiology: Cardiothoracic Imaging. 2020;2(2):e200075.
21. 21. Li K, Fang Y, Li W, Pan C, Qin P, Zhong Y, et al. CT image visual quantitative evaluation and clinical classification of coronavirus disease (COVID-19). European radiology. 2020:1-10.
22. 22. Leonardi A, Scipione R, Alfieri G, Petrillo R, Dolciami M, Ciccarelli F, et al. Role of computed tomography in predicting critical disease in patients with covid-19 pneumonia: A retrospective study using a semiautomatic quantitative method. European journal of radiology. 2020;130:109202.
23. 23. Sun D, Li X, Guo D, Wu L, Chen T, Fang Z, et al. CT quantitative analysis and its relationship with clinical features for assessing the severity of patients with COVID-19. Korean journal of radiology. 2020;21(7):859.
24. 24. Chen L-D, Zhang Z-Y, Wei X-J, Cai Y-Q, Yao W-Z, Wang M-H, et al. Association between cytokine profiles and lung injury in COVID-19 pneumonia. Respiratory Research. 2020;21(1):1-8.
25. 25. Francone M, Iafrate F, Masci GM, Coco S, Cilia F, Manganaro L, et al. Chest CT score in COVID-19 patients: correlation with disease severity and short-term prognosis. European radiology. 2020;30(12):6808-17.
26. 26. Zhang J, Meng G, Li W, Shi B, Dong H, Su Z, et al. Relationship of chest CT score with clinical characteristics of 108 patients hospitalized with COVID-19 in Wuhan, China. Respiratory research. 2020;21(1):1-11.
27. 27. Li K, Chen D, Chen S, Feng Y, Chang C, Wang Z, et al. Predictors of fatality including radiographic findings in adults with COVID-19. Respiratory research. 2020;21(1):1-10.
28. 28. Xu PP, Tian RH, Luo S, Zu ZY, Fan B, Wang XM, et al. Risk factors for adverse clinical outcomes with COVID-19 in China: a multicenter, retrospective, observational study. Theranostics. 2020;10(14):6372.
29. 29. Zhang R, Ouyang H, Fu L, Wang S, Han J, Huang K, et al. CT features of SARS-CoV-2 pneumonia according to clinical presentation: a retrospective analysis of 120 consecutive patients from Wuhan city. European radiology. 2020;30(8):4417-26.
30. 30. Galloway JB, Norton S, Barker RD, Brookes A, Carey I, Clarke BD, et al. A clinical risk score to identify patients with COVID-19 at high risk of critical care admission or death: an observational cohort study. Journal of Infection. 2020;81(2):282-8.
31. 31. Schalekamp S, Huisman M, van Dijk RA, Boomsma MF, Freire Jorge PJ, de Boer WS, et al. Model-based prediction of critical illness in hospitalized patients with COVID-19. Radiology. 2021;298(1):E46-E54.
32. 32. Hui TC, Khoo HW, Young BE, Mohideen SMH, Lee YS, Lim CJ, et al. Clinical utility of chest radiography for severe COVID-19. Quantitative imaging in medicine and surgery. 2020;10(7):1540.
33. 33. Kuo BJ, Lai YK, Tan MLM, Goh X-YC. Utility of Screening Chest Radiographs in Patients with Asymptomatic or Minimally Symptomatic COVID-19 in Singapore. Radiology. 2021;298(3):E131-E40.
34. 34. Prokop M, Van Everdingen W, van Rees Vellinga T, Quarles van Ufford H, Stöger L, Beenen L, et al. CO-RADS: a categorical CT assessment scheme for patients suspected of having COVID-19—definition and evaluation. Radiology. 2020;296(2):E97-E104.
35. 35. Kanne JP, Bai H, Bernheim A, Chung M, Haramati LB, Kallmes DF, et al. COVID-19 imaging: What we know now and what remains unknown. Radiology. 2021:204522.
36. 36. Salehi S, Abedi A, Balakrishnan S, Gholamrezanezhad A. Coronavirus disease 2019 (COVID-19) imaging reporting and data system (COVID-RADS) and common lexicon: a proposal based on the imaging data of 37 studies. European radiology. 2020;30(9):4930-42.
37. 37. Gezer NS, Ergan B, Barış MM, Appak Ö, Sayıner AA, Balcı P, et al. COVID-19 S: A new proposal for diagnosis and structured reporting of COVID-19 on computed tomography imaging. Diagnostic and Interventional Radiology. 2020;26(4):315.
38. 38. Byrne D, Neill SBO, Müller NL, Müller CIS, Walsh JP, Jalal S, et al. RSNA expert consensus statement on reporting chest CT findings related to COVID-19: interobserver agreement between chest radiologists. Canadian Association of Radiologists Journal. 2021;72(1):159-66.
39. 39. Bellini D, Panvini N, Rengo M, Vicini S, Lichtner M, Tieghi T, et al. Diagnostic accuracy and interobserver variability of CO-RADS in patients with suspected coronavirus disease-2019: a multireader validation study. European radiology. 2020:1-9.
40. 40. Hare S, Rodrigues J, Nair A, Jacob J, Upile S, Johnstone A, et al. The continuing evolution of COVID-19 imaging pathways in the UK: a British Society of Thoracic Imaging expert reference group update. Clinical radiology. 2020;75(6):399-404.
41. 41. Litmanovich DE, Chung M, Kirkbride RR, Kicska G, Kanne JP. Review of chest radiograph findings of COVID-19 pneumonia and suggested reporting language. Journal of thoracic imaging. 2020;35(6):354-60.
42. 42. Hare S, Tavare A, Dattani V, Musaddaq B, Beal I, Cleverley J, et al. Validation of the British Society of Thoracic Imaging guidelines for COVID-19 chest radiograph reporting. Clinical radiology. 2020;75(9):710. e9-. e14.
43. 43. Fang Y, Zhang H, Xie J, Lin M, Ying L, Pang P, et al. Sensitivity of chest CT for COVID-19: comparison to RT-PCR. Radiology. 2020;296(2):E115-E7.
44. 44. Sharfstein JM, Becker SJ, Mello MM. Diagnostic testing for the novel coronavirus. Jama. 2020;323(15):1437-8.
45. 45. Al-Tawfiq JA, Memish ZA. Diagnosis of SARS-CoV-2 infection based on CT scan vs RT-PCR: reflecting on experience from MERS-CoV. Journal of Hospital Infection. 2020;105(2):154-5.
46. 46. Chen D, Jiang X, Hong Y, Wen Z, Wei S, Peng G, et al. Can chest CT features distinguish patients with negative from those with positive initial RT-PCR results for coronavirus disease (COVID-19)? American Journal of Roentgenology. 2021;216(1):66-70.
47. 47. Ai T, Yang Z, Hou H, Zhan C, Chen C, Lv W, et al. Correlation of chest CT and RT-PCR testing for coronavirus disease 2019 (COVID-19) in China: a report of 1014 cases. Radiology. 2020;296(2):E32-E40.
48. 48. Wang Y, Dong C, Hu Y, Li C, Ren Q, Zhang X, et al. Temporal changes of CT findings in 90 patients with COVID-19 pneumonia: a longitudinal study. Radiology. 2020;296(2):E55-E64.
49. 49. Eng J, Bluemke DA. Imaging publications in the COVID-19 pandemic: applying new research results to clinical practice. Radiology. 2020;297(1):E228-E31.
50. 50. Kim H, Hong H, Yoon SH. Diagnostic performance of CT and reverse transcriptase polymerase chain reaction for coronavirus disease 2019: a meta-analysis. Radiology. 2020;296(3):E145-E55.
51. 51. Islam N, Salameh J-P, Leeflang MM, Hooft L, McGrath TA, Pol CB, et al. Thoracic imaging tests for the diagnosis of COVID‐19. Cochrane Database of Systematic Reviews. 2020(11).
52. 52. Li L, Qin L, Xu Z, Yin Y, Wang X, Kong B, et al. Using artificial intelligence to detect COVID-19 and community-acquired pneumonia based on pulmonary CT: evaluation of the diagnostic accuracy. Radiology. 2020;296(2):E65-E71.
53. 53. Bai HX, Wang R, Xiong Z, Hsieh B, Chang K, Halsey K, et al. Artificial intelligence augmentation of radiologist performance in distinguishing COVID-19 from pneumonia of other origin at chest CT. Radiology. 2020;296(3):E156-E65.
54. 54. Mei X, Lee H-C, Diao K-y, Huang M, Lin B, Liu C, et al. Artificial intelligence–enabled rapid diagnosis of patients with COVID-19. Nature medicine. 2020;26(8):1224-8.
55. 55. Zhang K, Liu X, Shen J, Li Z, Sang Y, Wu X, et al. Clinically applicable AI system for accurate diagnosis, quantitative measurements, and prognosis of COVID-19 pneumonia using computed tomography. Cell. 2020;181(6):1423-33. e11.
56. 56. Murphy K, Smits H, Knoops AJ, Korst MB, Samson T, Scholten ET, et al. COVID-19 on chest radiographs: a multireader evaluation of an artificial intelligence system. Radiology. 2020;296(3):E166-E72.
57. 57. Li MD, Arun NT, Gidwani M, Chang K, Deng F, Little BP, et al. Automated assessment of COVID-19 pulmonary disease severity on chest radiographs using convolutional Siamese neural networks. medRxiv. 2020.
58. 58. Tsai EB, Simpson S, Lungren M, Hershman M, Roshkovan L, Colak E, et al. The RSNA International COVID-19 Open Annotated Radiology Database (RICORD). Radiology. 2021:203957.
59. 59. Lim W, Le Gal G, Bates SM, Righini M, Haramati LB, Lang E, et al. American Society of Hematology 2018 guidelines for management of venous thromboembolism: diagnosis of venous thromboembolism. Blood advances. 2018;2(22):3226-56.
60. 60. Smith M, Hayward S, Innes S, Miller A. Point‐of‐care lung ultrasound in patients with COVID‐19–a narrative review. Anaesthesia. 2020;75(8):1096-104.
61. 61. Zuckier LS, Moadel RM, Haramati LB, Freeman LM. Diagnostic evaluation of pulmonary embolism during the COVID-19 pandemic. Journal of Nuclear Medicine. 2020;61(5):630-1.
62. 62. Helms J, Tacquard C, Severac F, Leonard-Lorant I, Ohana M, Delabranche X, et al. High risk of thrombosis in patients with severe SARS-CoV-2 infection: a multicenter prospective cohort study. Intensive care medicine. 2020;46(6):1089-98.
63. 63. Kaminetzky M, Moore W, Fansiwala K, Babb JS, Kaminetzky D, Horwitz LI, et al. Pulmonary embolism on CTPA in COVID-19 patients. Radiology Cardiothoracic Imaging. 2020;2(4).
64. 64. Bilaloglu S, Aphinyanaphongs Y, Jones S, Iturrate E, Hochman J, Berger JS. Thrombosis in hospitalized patients with COVID-19 in a New York City health system. Jama. 2020;324(8):799-801.
65. 65. Saba L, Sverzellati N. Is COVID evolution due to occurrence of pulmonary vascular thrombosis? Journal of thoracic imaging. 2020.
66. 66. Raptis CA, Hammer MM, Henry TS, Hope MD, Schiebler ML, Van Beek EJ. What Do We Really Know About Pulmonary Thrombosis in COVID-19 Infection? : LWW; 2020.
67. 67. Van Dam L, Kroft L, Van Der Wal L, Cannegieter S, Eikenboom J, De Jonge E, et al. Clinical and computed tomography characteristics of COVID-19 associated acute pulmonary embolism: A different phenotype of thrombotic disease? Thrombosis research. 2020;193:86-9.
68. 68. Cavagna E, Muratore F, Ferrari F. Pulmonary thromboembolism in COVID-19: venous thromboembolism or arterial thrombosis? Radiology: Cardiothoracic Imaging. 2020;2(4):e200289.
69. 69. Lax SF, Skok K, Zechner P, Kessler HH, Kaufmann N, Koelblinger C, et al. Pulmonary arterial thrombosis in COVID-19 with fatal outcome: results from a prospective, single-center, clinicopathologic case series. Annals of internal medicine. 2020;173(5):350-61.
70. 70. Fox SE, Akmatbekov A, Harbert JL, Li G, Brown JQ, Vander Heide RS. Pulmonary and cardiac pathology in African American patients with COVID-19: an autopsy series from New Orleans. The Lancet Respiratory Medicine. 2020;8(7):681-6.
71. 71. Ackermann M, Verleden SE, Kuehnel M, Haverich A, Welte T, Laenger F, et al. Pulmonary vascular endothelialitis, thrombosis, and angiogenesis in Covid-19. New England Journal of Medicine. 2020;383(2):120-8.
72. 72. D'Amico G, Muñoz‐Félix JM, Pedrosa AR, Hodivala‐Dilke KM. “Splitting the matrix”: intussusceptive angiogenesis meets MT 1‐MMP. EMBO molecular medicine. 2020;12(2):e11663.
73. 73. Lang M, Som A, Mendoza DP, Flores EJ, Reid N, Carey D, et al. Hypoxaemia related to COVID-19: vascular and perfusion abnormalities on dual-energy CT. The Lancet Infectious Diseases. 2020;20(12):1365-6.
74. 74. Oudkerk M, Büller HR, Kuijpers D, van Es N, Oudkerk SF, McLoud T, et al. Diagnosis, prevention, and treatment of thromboembolic complications in COVID-19: report of the National Institute for Public Health of the Netherlands. Radiology. 2020;297(1):E216-E22.
75. 75. Ayerbe L, Risco C, Ayis S. The association between treatment with heparin and survival in patients with Covid-19. Journal of thrombosis and thrombolysis. 2020;50:298-301.
76. 76. Puntmann VO, Carerj ML, Wieters I, Fahim M, Arendt C, Hoffmann J, et al. Outcomes of cardiovascular magnetic resonance imaging in patients recently recovered from coronavirus disease 2019 (COVID-19). JAMA cardiology. 2020;5(11):1265-73.
77. 77. Huang L, Zhao P, Tang D, Zhu T, Han R, Zhan C, et al. Cardiac involvement in patients recovered from COVID-2019 identified using magnetic resonance imaging. Cardiovascular Imaging. 2020;13(11):2330-9.
78. 78. Rajpal S, Tong MS, Borchers J, Zareba KM, Obarski TP, Simonetti OP, et al. Cardiovascular magnetic resonance findings in competitive athletes recovering from COVID-19 infection. JAMA cardiology. 2021;6(1):116-8.
79. 79. Wilson SJ, Connolly MJ, Elghamry Z, Cosgrove C, Firoozi S, Lim P, et al. Effect of the COVID-19 pandemic on ST-segment–elevation myocardial infarction presentations and in-hospital outcomes. Circulation: Cardiovascular Interventions. 2020;13(7):e009438.
80. 80. Garcia S, Albaghdadi MS, Meraj PM, Schmidt C, Garberich R, Jaffer FA, et al. Reduction in ST-segment elevation cardiac catheterization laboratory activations in the United States during COVID-19 pandemic. Journal of the American College of Cardiology. 2020;75(22):2871-2.
81. 81. Kicska G, Litmanovich DE, Ordovas KG, Young PM, Dennie C, Truong QA, et al. Statement from the North American Society for Cardiovascular Imaging on imaging strategies to reduce the scarcity of healthcare resources during the COVID-19 outbreak. The international journal of cardiovascular imaging. 2020;36:1387-93.